no code implementations • 20 Apr 2022 • Saeed Khan, Bryce A. Primavera, Jeff Chiles, Adam N. McCaughan, Sonia M. Buckley, Alexander N. Tait, Adriana Lita, John Biesecker, Anna Fox, David Olaya, Richard P. Mirin, Sae Woo Nam, Jeffrey M. Shainline
Superconducting optoelectronic hardware is being explored as a path towards artificial spiking neural networks with unprecedented scales of complexity and computational ability.
no code implementations • 30 Oct 2020 • Bhavin J. Shastri, Alexander N. Tait, Thomas Ferreira de Lima, Wolfram H. P. Pernice, Harish Bhaskaran, C. David Wright, Paul R. Prucnal
Research in photonic computing has flourished due to the proliferation of optoelectronic components on photonic integration platforms.
no code implementations • 17 Jul 2019 • Thomas Ferreira de Lima, Alexander N. Tait, Hooman Saeidi, Mitchell A. Nahmias, Hsuan-Tung Peng, Siamak Abbaslou, Bhavin J. Shastri, Paul R. Prucnal
Here, we examine modulator-based photonic neuron circuits with passive and active transimpedance gains, with special attention to the sources of noise propagation.
1 code implementation • 23 Apr 2019 • Viraj Bangari, Bicky A. Marquez, Heidi B. Miller, Alexander N. Tait, Mitchell A. Nahmias, Thomas Ferreira de Lima, Hsuan-Tung Peng, Paul R. Prucnal, Bhavin J. Shastri
Convolutional Neural Networks (CNNs) are powerful and highly ubiquitous tools for extracting features from large datasets for applications such as computer vision and natural language processing.
no code implementations • 5 Nov 2016 • Alexander N. Tait, Thomas Ferreira de Lima, Ellen Zhou, Allie X. Wu, Mitchell A. Nahmias, Bhavin J. Shastri, Paul R. Prucnal
At increased scale, Neuromorphic silicon photonics could access new regimes of ultrafast information processing for radio, control, and scientific computing.